Moving beyond simulation and learning: Unveiling the potential of complexity data science

Complexity science is a multidisciplinary field that examines various aspects of complex systems. While complexity science places a significant emphasis on simulation, it has a somewhat neglectful treatment of learning. In this paper, we explore a recent example of the potential synergy between simulation and learning, illustrated by the concept of digital twins. We argue that integrating simulation and learning holds significant promise beyond the scope of digital twins alone. In our view, the general amalgamation of complexity science and data science heralds the dawn of a distinct and innovative field in its own right, which we call complexity data science.